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Course / Course Details
By - CYSEC Academy
Basic understanding of programming (preferably Python)
Foundational knowledge of mathematics (algebra, probability, and statistics)
Familiarity with data structures and algorithms is helpful but not mandatory
A laptop with internet access and the ability to install software
This course introduces participants to the foundational concepts, techniques, and tools of Artificial Intelligence (AI) and Machine Learning (ML). Learners will explore how machines learn from data, make predictions, and improve decision-making processes. The course covers key algorithms such as linear regression, decision trees, neural networks, and unsupervised learning methods.
By the end of this course, participants will be able to:
Understand core AI concepts and the machine learning lifecycle
Differentiate between supervised, unsupervised, and reinforcement learning
Build, train, and evaluate machine learning models using Python libraries such as scikit-learn and TensorFlow
Analyze datasets and select appropriate algorithms based on the problem type
Implement projects such as spam detection, image classification, or customer segmentation
Module 1
Module 2
Module 3
Module 4
Module 5
Module 6
Module 7
Module 8
Module 9
Module 10
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